Statistical Significance: Maximum Likelihood Estimation and Confidence Intervals

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Statistics: Hypothesis Testing & Confidence Intervals

Covers hypothesis testing, confidence intervals, data distributions, and statistical significance in data analysis.

Detection & Estimation

Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.

Probability and Statistics

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Probability and Statistics: Independence and Conditional Probability

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

Statistical Theory: Fundamentals

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

Statistical Theory: Inference and Optimality

Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.

Describing Data: Statistics and Hypothesis Testing

Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.

Linear Regression: Ozone Data Analysis

Explores linear regression analysis of ozone data using statistical models.

Probability and Statistics: Fundamental Theorems

Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.

Testing: t-tests

Covers t-tests, p-values calculation, and comparison of coefficients.